I would like to acknowledge the Traditional Owners of Australia and recognise their continuing connection to land, water and culture. I am currently lecturing on the land of the Gadigal people of the Eora Nation and pay my respects to their Elders, past, present and emerging.
Emergency procedures
In the unlikely event of an emergency, we may need to evacuate the building.
If we need to evacuate, we will ask you to take your belongings and follow the green exit signs.
We will move a safe distance from the building and maintain physical distancing whilst waiting until the emergency is over.
In some circumstances, we might be asked to remain inside the building for our own safety. We call this a lockdown or shelter-in-place. More information is available at www.sydney.edu.au/emergency.
Health and safety advice
Illness & absence
If you become ill during the semester, or need to stay at home or need to be absent for a period, please notify your unit of study coordinator.
Visit the Student life, wellbeing and support webpage to find out about the student services, resources and events available to support you while you study:
Health and wellbeing
Academic Support
Personal support
Getting connected
Questions about getting started this semester? Come visit us at a Welcome Hub in Anderson Stuart or Carslaw Building.
Safer Communities Office
Support and case management for people who have experienced sexual misconduct, domestic/family violence, bullying/harassment or issues relating to modern slavery.
Contact the team:
8:30 am to 5:30 pm Monday to Friday, Sydney local time
phone: +61 2 8627 6808
email: safer-communities.officer@sydney.edu.au.
campus: Level 5, Jane Foss Russell building, City Road, Darlington Campus
Make a report:
Visit the website to make a complaint or disclosure of sexual misconduct to the University.
Support services
The Office of Educational Integrity: Report anonymously or seek advice: educational.integrity@sydney.edu.au
Learning Hub:
The Learning Hub (Academic Language and Learning) offers workshops, online resources and individual consultations on study and writing skills.
The Learning Hub (Mathematics) offers bridging courses, drop-in services and online resources.
Library:
Check out the Library’s online resources and referencing and citation styles.
You can also chat with a Peer Learning Advisor about your studies, including referencing questions
Counselling and mental health support: The University’s Counselling and Psychological Services provide self and time-management workshops and online resources.
Special Arrangements and Consideration: Apply for special consideration if impacted by short-term illness or misadventure
Disability Services: Register for Disability Support
Student organisations:
SRC (undergraduate students)
SUPRA (postgraduate students)
Do you have a disability that impacts on your studies?
You may not think of yourself as having a ‘disability’, but the definition under the Disability Discrimination Act (1992) is broad and includes temporary or chronic medical conditions, physical or sensory disabilities, psychological conditions and learning disabilities.
In order to get assistance, students need to register with Disability Services. It is advisable to do this as early as possible. Please contact us or review our website to find out more.
Academic integrity refers to behaving honestly, ethically and responsibly in relation to all elements of your study at the university, including assessments.
Always submit your own work, sit your own tests, and take your own examinations.
Acknowledge any contributions in your assignment which are not your original thoughts, ideas or words.
Academic Honesty Education Module – all commencing students must complete by census date. Continuing students can self-enrol at any time.
What is academic dishonesty?
The following are some behaviours that are academically dishonest:
Plagiarism (this is the most common form)
Collusion or illegitimate co-operation
Recycling (using your own work from previous assessments)
Cheating, including contract cheating
sharing questions or accessing solutions on online “help sites”
receiving coaching from a private tutoring company on how to complete an assignment
asking someone else to write your assignment (for payment or not)
Exam cheating (using prohibited materials, working with others)
Fabrication or falsification of sources, data or results
What are the consequences?
The University has strong mechanisms for detection of potential academic dishonesty.
Suspected breaches are reported to the faculty educational integrity team for investigation.
The University is deeply committed to ensuring the integrity of its educational programs and treats integrity breaches seriously. As a result, the academic consequences for cheating are numerous.
You may:
need to resubmit a task with a mark penalty or
receive a 0 for the assessment or even the unit of study
be suspended or even excluded from your studies for serious misconduct
Understanding contract cheating
Commercial cheating services are ILLEGAL in Australia. Illegal cheating services offer to:
Sell you essays, assignments, study notes or exams
Ask you to upload previous work from your course
Sit exams on your behalf
If you use cheating services, you can face disciplinary action in accordance with USYD’s policies. Resulting action can include:
Failing the unit of study or course
Suspension or exclusion from your studies
Losing your professional accreditation
Being blackmailed by cheating service operators
For international students, losing your visa
Be aware of illegitimate services
Be aware of any services that are not affiliated with the University.
In the online environment, malicious organisations masquerading as “online help sites and platforms” are preying on students.
These organisations may pressure you to pay for online assistance, then turn to blackmail when you change your mind.
Essays or solutions bought from the internet are usually poor quality, badly written and often wrong.
You won’t acquire the skills and knowledge required for your degree, making it difficult to complete further assessments.
Exams and mid semester test will be face-to-face unless we experience circumstances that prohibit this.
ProctorU software is used to monitor your conduct during an exam. Incidents are flagged to the University and reviewed for breaches of academic integrity.
The exam will be compromised if you:
Use prohibited materials (e.g., headphones, mobile phones, etc)
Communicate or collude with others
Seek help via a third party, the university’s sites or help sites
To ensure success, we recommend the following tips:
Sit directly in front of the camera
Review the online test support site on Canvas
Know what materials are permitted during the exam.
Have your ID ready
Don’t wear headphones, either wired or unwired
Contact information
Floris van Ogtrop - unit coordinator
Room 306, Level 3, Biomedical Bldg, Australian Technology Park, Eveleigh
Tutors & Demonstrators: mainly Honours/Masters/PhD students or PhD graduates
Timetable and locations
Lecture (recorded) - Monday 12pm ABS Lecture Theatre 1040 and Tuesday 9 am ABS Lecture Theatre 1130
Tutorials – 1 hour per week self guided study using provided video to complete in allocated time prior to practical
Computer Labs (Australia Technology Park) – 2 hour computer lab directly following self-study; see personal timetable
Australian Technology Park
We have programmed in 30 minutes travel time and if you complete the tutorial prior to the scheduled time, you will have an extra hour.
There is a shuttle service that runs intermittently.
Learning outcomes
LO1. Apply Statistical Tools Using R and Excel: Demonstrate proficiency in utilizing R and Excel to effectively process, describe, and analyse data from simple experiments, showing skill in applying these tools to real-world data sets.
LO2. Evaluate Probability Concepts and Calculations: Evaluate and interpret the concept of probability, proficiently calculate probabilities by correctly applying probability laws and theoretical results and assess their significance in experimental contexts.
LO3. Synthesize Knowledge for Experimental Inference: Integrate understanding of experimental inference to discern and select the most appropriate statistical test (including 1-sample, 2-sample, chi-square, and non-parametric tests) for various types of experimental data, showing the ability to tailor statistical approaches to specific research questions.
LO4. Model Relationships Using Linear and Non-Linear Functions: Construct and apply both linear and non-linear models to describe relationships between variables using R and Excel, demonstrating creativity in developing models that effectively represent complex data patterns.
LO5. Communicate Statistical Findings Effectively: Articulate statistical and modelling results clearly and convincingly in both written scientific reports and oral presentations, working effectively as an individual and collaboratively in a team, showcasing the ability to convey complex information to varied audiences.
UoS outline
Week 01 - Data: Introduction and Scientific Method
Week 02 - Data: Exploratory Data Analysis
Week 03 - Data: Normal and discrete distributions
Week 04 - Data: Sampling distributions
Week 05 - Inference: 1-sample tests
Week 06 - Inference: 2-sample tests
Week 07 - Inference:Non-parametric tests 1
Week 08 - Inference:Non-parametric tests 2
Week 09 - Modelling: Describing relationships
Week 10 - Modelling: Linear functions
Week 11 - Modelling: Linear functions – multiple predictors
Week 12 - Modelling: Non-linear functions
Week 13 - Revision Past exam questions.
Assessment
Projects
Project 1 (individual 10%): Exploring data - week 5 - 500 words
Project 2 (individual 10%): Making decisions about data - week 10 - 800 words
Project 3 (group 10% + Peer assessment 5%): Modelling relationships in data - due week 13 - 5 minute group presentation
In class tests - practicals
Early Feedback Quiz (individual 5%): Describing data with R - Week 3 - 15 minutes
Coding and data skills evaluation (individual 15%): Analysing data with R - Week 08 - 50 minutes
Lecture attendance is not compulsory but strongly recommended as we do make interactive classes. Lectures will be recorded.
A minimum 80% attendance is required in practicals
Practical attendance is very important for group work as well as learning.
There is a “statistically significant” correlation between class attendance and performance in this unit.
Attendance
Reference material
Lecture slides on Canvas
Statistics texts: see reading list on Canvas
Mead R, Curnow RN, Hasted AM (2002) ‘Statistical methods in agriculture and experimental biology.’ [e-book – see Reading List in Canvas]
Quinn GP, Keough MJ (2002) ‘Experimental design and data analysis for biologists.’ [e-book – see Reading List in Canvas]
Murray, L. (2010) ‘Biostatistical Design and Analysis Using R: a practical guide.’ [e-book – see Reading List in Canvas]
Unit of Study Notes: See Canvas
There are heaps of online free texts and online resources that use R - see for example https://leanpub.com/os
chatGPT, rtutor.ai, co-pilot in RStudio
Need help?
Ed discussion - Q&A discussion: This is the quickest way to get help
Drop-in sessions: TBA
Demonstrators: We have a great teaching team of honours and postgraduate students who are all good with R and Stats! Please remember though, they are also learning to teach and so may not have an answer for everything!
Applied statistics units
Core for most of you
1st year: Introduction to statistical methods (ENVX1002)
2nd year: Applied statistical methods (ENVX2001)
Elective statistics units offered in SOLES
2nd or 3rd year: Statistics in the natural sciences (ENVX3002)
Honours: Experimental Design and Data Analysis (SCIE4002)
Statistical software packages
R is Free and Open Source
R has become a main stream and very powerful statistical tool
Download from http://cran.r-project.org/
> 6,000 packages for specialised tasks or modelling